Understanding
Experience
Human behaviour is not random. It emerges from underlying emotional and cognitive states that continuously shape attention, motivation, decision-making and engagement.
Yet while modern systems can observe behaviour, they typically have little visibility into the experiences driving it.
Contemporary neuroscience increasingly views emotion not as a fixed category, but as something actively constructed by the brain. Experiences emerge from continuous interpretations of context, physiology and behaviour rather than simple emotional labels such as "happy" or "sad".
This perspective suggests that behaviour alone may tell only part of the story. To understand why people act as they do, we also need to understand the experiences shaping those actions.
nX10's scientific work begins with a simple question:
What if technology could become sensitive to the experiences that shape behaviour rather than behaviour alone?
The Science of Attunement
nx10 creates opportunities for earlier, more supportive and more human-centred interactions in the technology we use everyday.
Attunement describes a system's ability to recognise meaningful changes in someone's experience and respond appropriately.
Rather than waiting for behaviour to signal a problem, attuned systems can respond to shifts as they emerge.
An Interdisciplinary Foundation
nX10's work sits at the intersection of four core pillars:
Computational neuroscience
Machine learning
Cognitive science
Human behaviour
Together, these fields provide new ways to understand the relationship between internal experience and outward behaviour.
Responsible by Design
nX10 is designed to understand interaction patterns rather than personal content.
The platform does not require access to messages, conversations, passwords, images or semantic content. This approach helps support privacy while enabling scientific investigation into experience.
Science First
nX10 is being developed through a structured programme of scientific validation and real-world testing.
We believe meaningful innovation requires evidence, not assumptions.